A machine learning approach to infer the accreted stellar mass fractions of central galaxies in the TNG100 simulation
| Title | A machine learning approach to infer the accreted stellar mass fractions of central galaxies in the TNG100 simulation |
| Publication Type | Journal Article |
| Year of Publication | 2022 |
| Authors | Shi, R, Wang, W, Li, Z, Han, J, Shi, J, Rodriguez-Gomez, V, Peng, Y, Li, Q |
| Journal | \mnras |
| Date Published | jun |
| Keywords | Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics, cosmology: dark matter, galaxies: evolution, galaxies: statistics, galaxies: stellar content, method: data analysis, method: numerical |
| DOI | 10.1093/mnras/stac1541 |
English